Overview

The future of intelligence has arrived. In OSINT 2.0: Building Autonomous AI Intelligence Systems, author Odrin Vassilev reveals how to create self-learning, AI-driven ecosystems that collect, analyze, and act on open-source information-without constant human control. This third volume in the OSINT 2.0 trilogy moves far beyond manual research or simple automation. It's a full-stack blueprint for building autonomous AI intelligence operations capable of real-time monitoring, threat detection, and decision support across the entire web. From Analyst to Architect You've mastered the fundamentals (Book 1) and advanced AI tradecraft (Book 2). Now you'll learn to design, deploy, and manage your own AI intelligence systems that think, adapt, and evolve. Step-by-step, Vassilev shows you how to: Architect Intelligence Pipelines: Integrate APIs, machine-learning models, and OSINT tools into automated workflows that continuously collect and analyze data. Build Autonomous Agents: Create AI bots that can search, filter, verify, and summarize information in real time using large-language models and vector databases. Develop Scalable Frameworks: Use Python, no-code platforms, or orchestration tools to manage multiple AI agents working collaboratively on intelligence tasks. Implement Continuous Threat Intelligence: Detect cyber threats, disinformation campaigns, and network anomalies with autonomous monitoring systems. Fuse Multi-Source Data: Combine surface, deep, and dark-web inputs into unified dashboards that deliver actionable insights automatically. Secure & Govern Your Systems: Apply ethical, legal, and technical safeguards to ensure compliance, data integrity, and operational transparency. Each chapter blends AI engineering, OSINT methodology, and practical deployment guidance, giving you both the strategy and the code-level perspective needed to bring autonomous intelligence to life. Inside the Autonomous Intelligence Lab You'll explore how to: Connect AI models like GPT, Claude, or Gemini to investigative APIs and open data repositories. Implement real-time alerting systems that flag new threats or emerging narratives. Build knowledge graphs and embedding-based retrieval systems that learn from data over time. Deploy cloud-based or local AI intelligence nodes for 24/7 monitoring and correlation. Create custom dashboards for visualization, auditing, and human-in-the-loop validation. Every example is explained with clarity, helping you bridge the gap between conceptual design and real-world execution. Who This Book Is For This volume is for professionals ready to move from analysis to autonomous operations: Cyber-intelligence analysts seeking scalable, always-on threat detection. Investigators and SOC teams automating data fusion and alerting. Developers and data scientists integrating AI into investigative systems. Journalists and researchers building live monitoring tools for large data streams. Leaders and strategists shaping next-generation intelligence infrastructures. If you've ever imagined building an AI that can investigate, learn, and report-this is the guide that shows you how. Why OSINT 2.0 Changes Everything Autonomous intelligence isn't science fiction; it's the logical next step in the OSINT evolution. By merging machine autonomy with human judgment, organizations can react to threats faster, verify facts instantly, and make data-driven decisions at scale.

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